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Extending a model of how teams learn, this paper aims to present a model of multiteam system (MTS) learning, comparing similarities and differences between how MTSs learn and how component teams learn. The paper describes the value of adaptive, generative and transformative learning for increasing MTS development over time.

The model proposes that environmental demands trigger adaptive, generative and transformative MTS learning, which is further increased by the MTS’s readiness to learn. Learning can happen during performance episodes and during hiatus periods between performance episodes.

Learning triggers coupled with readiness to learn and the cycle and phase of MTS process influence the learning process (adaptive, generative or transformative), which in turn influences the learning outcomes.

The study offers a number of research propositions with the idea that the model and propositions will stimulate research in this area.

This model allows MTS and component team leaders and facilitators to recognize that MTS learning is a process that is needed to help component teams work together and help the MTS as a whole perform in current and future situations, thereby improving MTS effectiveness.

Little attention has been given to the notion that MTSs learn and develop. This manuscript is the first to emphasize that MTSs learn and identify processes that can improve learning. Adaptive, generative and transformative processes describe how MTSs learn and produce changes in MTS structure and actions.

The aim of this study is to analyze a framework of team learning that includes three learning processes (adaptive, generative, and transformative), factors that stimulate these processes, and consequences of them. The variables provided a field study of the model.

In the field study, 69 project teams of 3 to 11 students and their instructors responded to surveys.

Positive learning stimuli were related to adaptive and generative learning processes, while negative stimuli were related to transformative learning processes. Learning processes were related to individual student learning outcomes. In addition, adaptive and generative learning processes were positively related to team and instructor ratings of outcome quality, while transformative learning was negatively related to team ratings of outcome quality.

The results were subject to the following limitations: cross‐sectional design, mostly self‐report measures, and the lack of control endemic to field research. As such, this study is viewed as an initial test of the team‐learning model in a field setting. Additional research, including longitudinal designs and experimental designs, are called for.

This study adds to the growing literature on group learning. Educators and managers need to be aware that there are different kinds of learning processes in which groups can engage and that these are stimulated to occur differently and have a different impact on outcomes.

Team learning is rarely assessed directly as a construct in its own right and there is a lack of empirical support delineating causes and consequences of team learning. This field study is a first step in this direction.

This study aims to examine the direct and moderating effects of generative learning on customer performance.

The authors test the relationships between customer relationship management (CRM) capabilities, generative learning, customer performance, and financial performance with a cross industry survey of CEOs and senior marketing executives from 199 firms. Partial least squares are used to estimate the parameters of the resulting model.

The results reveal that generative learning affects customer performance directly. Moreover, the interaction of CRM capabilities and generative learning contributes to customer performance. This finding suggests that firms need a well-developed generative learning orientation to fully benefit from translating new insights resulting from CRM capabilities into establishing, maintaining, and enhancing long-term associations with customers, and vice versa.

The main limitations are those that typically apply to cross-sectional surveys. Although several steps were taken to reduce the concern of key informant bias and common method variance, dependent and independent variables were collected from the same source at a single moment in time.

Ceteris paribus, an increase of generative learning orientation by one unit (seven-point scale) can command an increase of up to 7 percent of the average customer performance due to its direct and interaction effect. Because even small changes in customer performance have a strong impact on financial performance, this finding indicates a remarkable and substantial result for managers.

Though previous research provides evidence of the adaptive learning consequences of CRM, a review of the literature reveals a lack of studies that analyze the importance of generative learning orientation for successful CRM.

This paper examines activity‐based costing (ABC) as a tool for organizational learning. More specifically, it is suggested that ABC can help business organizations engage in adaptive as well as generative learning. ABC facilitates adaptive learning by supporting continuous improvement and the management of existing knowledge. It facilitates generative learning by supporting the development of a learning culture and the social context in which new mental models can be developed. Important guidelines for implementing ABC to enhance organizational learning are distilled from a mini case study of a health care services provider.

Multi-team systems (MTSs) are expected to respond effectively to complex challenges while remaining responsive and adaptable and preserving inter-team linking mechanisms. The leadership team of an MTS is expected to configure and reconfigure component teams to meet the unique needs of each situation and perform. How do they learn to do this? This paper, using a recent MTS learning theory as a basis, aims to begin to understand how MTSs learn and stimulate ideas for future research.

The authors use two case studies to address research questions. The first case was a snapshot in time, while the second case occurred over several months. Interviews, documents and participant observation were the data sources.

As suggested by theory, findings support the idea that learning triggers, the timing of the triggers and readiness to learn (RtL) affect the type of learning process that emerges. The cases showed examples of adaptive and generative team learning. Strong and clear triggers, occurring during performance episodes, led to adaptive learning. When RtL was high and triggers occurred during hiatus periods, the associated learning process was generative.

Using an available theoretical model and case studies, the research describes how MTS readiness to learn and triggers for learning affect MTS learning processes and how learning outcomes became codified in the knowledge base or structure of the MTS. This provides a framework for subsequent qualitative and quantitative research.

The purpose of this paper is to develop propositions for empirical validation regarding appropriate management planning and control systems (MPACS) in knowledge‐intensive organizations.

The propositions were developed from interviews with members of a knowledge‐intensive virtual organization that is known for its innovative practices regarding intellectual capital (IC) development and surveys from low to middle range managers, using a semi‐structured questionnaire, from a variety of companies. Trends in responses permitted us to identify issues of importance in developing innovative MPACS for knowledge‐intensive companies.

The paper proposes that two variables, the level of IC intensity and the uncertainty of knowledge, are important for determining the degree of adaptive versus generative characteristics that an organization's MPACS should contain. Regarding IC, the paper further proposes that organizations must give careful thought to ensure that both adaptive and generative characteristics are aligned with four MPACS elements of focus, commitment, capability, and learning.

As organizations develop programs to realize the potential from their intellectual capital, many fail to develop MPACS that are appropriate for knowledge‐intensive environments. MPACS should support knowledge creation, as well as knowledge sharing, and contain elements of both adaptive and generative systems.

This study aims to investigate a mediation model in which generative learning positively affects marketing innovation and both organizational control and relationship openness mediate the relationship between learning intent and generative learning of international joint ventures (IJVs) in emerging markets. We also decipher the degree of necessity of these factors for generative learning and of generative learning for marketing innovation.

A sample of 181 marketing managers of IJVs in Vietnam, an emerging market, was surveyed to collect data. Partial least squares structural equation modeling (PLS-SEM) was employed to test the net effect, and necessary condition analysis (NCA) was used to decipher the degree of necessity.

The PLS-SEM results demonstrate that the effect of learning intent on generative learning is fully mediated by organizational control and relationship openness, which in turn leads to marketing innovation. The NCA findings reveal that all three factors, namely learning intent, organizational control and relationship openness, serve as necessary conditions for generative learning. However, generative learning does not play the role of a necessary condition for marketing innovation.

The study findings suggest that IJVs in emerging markets should pay attention not only to the net effects of those factors but also to their degrees of necessity for generative learning in order to achieve marketing innovation.

The study contributes to the literature by confirming the mediating roles of organizational control and relationship openness in the relationship between learning intent and generative learning. Furthermore, it is among the first to decipher the degrees of necessity of these factors for generative learning and of generative learning for the marketing innovation of IJVs in emerging markets.

This paper aims to evaluate the behavior of micro and macro business networks in a trade show context. The following questions are addressed: How do business networks impact organizational learning at trade shows? Can relational ties between networks influence organizational learning? Does trust play a role between different network types and organizational learning?

The theoretical framework for this research is based on the broad spectrum of social exchange theory (Cropanzano and Mitchell, 2005; Foa and Foa, 1974, 1980; Kelley and Thibault, 1978; Kelley, 1997). Social exchange theory has several different interpretations; one common view of this theory involves a series of interactions that result in obligations for the participating members (Emerson, 1976; Cropanzano and Mitchell, 2005). This model extends the Levin and Cross (2004) model presented in their article, “strength of weak ties you can trust: the mediating role of trust in effective knowledge transfer”.

This paper is a review and synthesis of trade show, trust, organizational learning and business network literature. This conceptual paper concludes with eight propositions, which delve into connections between micro and macro networks, strong and weak ties in these networks and the effect on organizational learning. Trust is the mediating variable between networks and organizational learning. High levels of trust could change the learning approach (adaptive, generative or transformative) of the different networks.

The propositions integrate extant research on trade shows and will guide future research regarding the relationship between types of business networks, trust and organizational learning.

This conceptual paper looks at trade shows from a network perspective; specifically, how do trade show networks impact organizational learning. Trade show participation results in different approaches to organizational learning, which can be modified based on the level of trust that exists between network members. Trade show participation enables both adaptive and generative learning. However, atypical interactions between business networks occasionally produce transformative learning.

This conceptual paper offers an innovative approach to trade show research by analyzing the relationship between trade shows and organizational learning from a network perspective, using trust as the mediating variable.

Students of organizations are beginning to recognize the importance of continuous learning in organizations, but to date the concept is not well understood, particularly in terms of how the learning of individuals is related to the learning that takes place in groups, which is related to the learning that occurs in organizations (and all other combinations). To further our understanding, we offer the idea of continuous learning in organizations from a living system's perspective. We view individuals, groups, and organizations as living systems nested in a hierarchy. We propose that living systems can learn in three ways: they can adapt, they can generate, and they can transform. Learning triggers from the environment spark learning, and this relationship is moderated by the system's readiness to learn. Readiness to learn is a function of the permeability of the system's boundaries, the system's stage of development, and the system's meta-systems perspective. Additional research questions are presented to explore learning flow between levels and to determine how the match between one system's pressure for change and another system's readiness to learn affects the emergence of adaptive, generative, and transformative learning. In addition, research questions are offered as a means to test these ideas and build grounded theory. Finally, using this model, the chapter presents three case studies and suggests diagnostic questions to analyze and facilitate continuous learning from a multi-level perspective.

In this response to Day and Tate (this volume) and Markham, Groesbeck, and Swan (this volume), we clarify the concept of continuous learning from a living system's perspective and address the evolution of adaptive, generative, and transformative learning. Further, we assert that a system's drive for homeostasis is actually a fluid, continuous learning process that may vary in the rate and direction of change. Environmental triggers, readiness for learning, and feedback provide leverage points for change and learning within and across individual, group, and organizational systems. Future research is needed to identify and study the effects of these leverage points on systems’ adaptive, generative, and transformative learning.